load datasets
Now let’s focus on samples with genotype data.
PTSD_diagnosis
sex 0 1 2092 7011
0 1300 552 0 0
1 3517 1631 0 0
519 0 0 1 0
8584 0 0 0 1
- What is a better trauma exposure measure we should use?
- Do we have CRP and other molecular markers measured?
- Do we have BMI and other anthropometric measurements?
| PSStotal |
|
|
|
< 0.001 |
| Â Â Â Mean (SD) |
6.288 (6.773) |
26.763 (9.411) |
12.784 (12.256) |
|
| Â Â Â Range |
0.000 - 47.000 |
4.250 - 51.000 |
0.000 - 51.000 |
|
| BDItotalscore |
|
|
|
< 0.001 |
| Â Â Â N-Miss |
134 |
85 |
219 |
|
| Â Â Â Mean (SD) |
9.864 (9.222) |
24.037 (11.890) |
14.320 (12.085) |
|
| Â Â Â Range |
0.000 - 63.000 |
0.000 - 59.000 |
0.000 - 63.000 |
|
| as.factor(BDI_CAT) |
|
|
|
< 0.001 |
| Â Â Â N-Miss |
134 |
85 |
219 |
|
| Â Â Â 0 |
3168 (84.1%) |
627 (36.3%) |
3795 (69.1%) |
|
| Â Â Â 1 |
600 (15.9%) |
1101 (63.7%) |
1701 (30.9%) |
|
| age |
|
|
|
0.458 |
| Â Â Â N-Miss |
16 |
13 |
29 |
|
| Â Â Â Mean (SD) |
39.927 (14.319) |
40.219 (12.564) |
40.020 (13.787) |
|
| Â Â Â Range |
18.000 - 78.000 |
18.000 - 70.000 |
18.000 - 78.000 |
|
| as.factor(sex) |
|
|
|
0.080 |
| Â Â Â N-Miss |
7 |
3 |
10 |
|
| Â Â Â 0 |
1034 (26.5%) |
441 (24.4%) |
1475 (25.9%) |
|
| Â Â Â 1 |
2861 (73.5%) |
1369 (75.6%) |
4230 (74.1%) |
|
| education |
|
|
|
0.072 |
| Â Â Â N-Miss |
20 |
18 |
38 |
|
| Â Â Â Mean (SD) |
1.887 (1.639) |
1.803 (1.620) |
1.860 (1.633) |
|
| Â Â Â Range |
0.000 - 6.000 |
0.000 - 6.000 |
0.000 - 6.000 |
|
| CTQTOT |
|
|
|
< 0.001 |
| Â Â Â N-Miss |
30 |
15 |
45 |
|
| Â Â Â Mean (SD) |
36.651 (14.087) |
49.652 (20.422) |
40.774 (17.445) |
|
| Â Â Â Range |
25.000 - 112.500 |
25.000 - 125.000 |
25.000 - 125.000 |
|
| as.factor(race_ethnic) |
|
|
|
< 0.001 |
| Â Â Â N-Miss |
16 |
18 |
34 |
|
| Â Â Â 0 |
3655 (94.1%) |
1633 (91.0%) |
5288 (93.1%) |
|
| Â Â Â 1 |
25 (0.6%) |
16 (0.9%) |
41 (0.7%) |
|
| Â Â Â 2 |
6 (0.2%) |
1 (0.1%) |
7 (0.1%) |
|
| Â Â Â 3 |
105 (2.7%) |
77 (4.3%) |
182 (3.2%) |
|
| Â Â Â 4 |
52 (1.3%) |
47 (2.6%) |
99 (1.7%) |
|
| Â Â Â 5 |
43 (1.1%) |
21 (1.2%) |
64 (1.1%) |
|
|
Controls (N=3902) |
Cases (N=1813) |
Overall (N=5715) |
| PSStotal |
|
|
|
| Mean (SD) |
6.29 (6.77) |
26.8 (9.41) |
12.8 (12.3) |
| Median [Min, Max] |
4.00 [0, 47.0] |
26.0 [4.25, 51.0] |
9.00 [0, 51.0] |
| BDItotalscore |
|
|
|
| Mean (SD) |
9.86 (9.22) |
24.0 (11.9) |
14.3 (12.1) |
| Median [Min, Max] |
7.35 [0, 63.0] |
23.0 [0, 59.0] |
11.0 [0, 63.0] |
| Missing |
134 (3.4%) |
85 (4.7%) |
219 (3.8%) |
| Age |
|
|
|
| Mean (SD) |
39.9 (14.3) |
40.2 (12.6) |
40.0 (13.8) |
| Median [Min, Max] |
41.0 [18.0, 78.0] |
42.0 [18.0, 70.0] |
41.0 [18.0, 78.0] |
| Missing |
16 (0.4%) |
13 (0.7%) |
29 (0.5%) |
| as.factor(sex) |
|
|
|
| 0 |
1034 (26.5%) |
441 (24.3%) |
1475 (25.8%) |
| 1 |
2861 (73.3%) |
1369 (75.5%) |
4230 (74.0%) |
| Missing |
7 (0.2%) |
3 (0.2%) |
10 (0.2%) |
| education |
|
|
|
| Mean (SD) |
1.89 (1.64) |
1.80 (1.62) |
1.86 (1.63) |
| Median [Min, Max] |
1.00 [0, 6.00] |
1.00 [0, 6.00] |
1.00 [0, 6.00] |
| Missing |
20 (0.5%) |
18 (1.0%) |
38 (0.7%) |
| Childhood trauma score |
|
|
|
| Mean (SD) |
36.7 (14.1) |
49.7 (20.4) |
40.8 (17.4) |
| Median [Min, Max] |
31.0 [25.0, 113] |
45.0 [25.0, 125] |
34.0 [25.0, 125] |
| Missing |
30 (0.8%) |
15 (0.8%) |
45 (0.8%) |
| as.factor(race_ethnic) |
|
|
|
| 0 |
3655 (93.7%) |
1633 (90.1%) |
5288 (92.5%) |
| 1 |
25 (0.6%) |
16 (0.9%) |
41 (0.7%) |
| 2 |
6 (0.2%) |
1 (0.1%) |
7 (0.1%) |
| 3 |
105 (2.7%) |
77 (4.2%) |
182 (3.2%) |
| 4 |
52 (1.3%) |
47 (2.6%) |
99 (1.7%) |
| 5 |
43 (1.1%) |
21 (1.2%) |
64 (1.1%) |
| Missing |
16 (0.4%) |
18 (1.0%) |
34 (0.6%) |


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